Automatically determining and implementing messaging characteristics using artificial intelligence techniques

Abstract

Methods, apparatus, and processor-readable storage media for automatically determining and implementing messaging characteristics using artificial intelligence techniques are provided herein. An example computer-implemented method includes determining one or more context-based messaging characteristics for at least one user device based on message-related data associated with the user device(s) and one or more software applications running on the user device(s); prioritizing at least one of multiple messages intended for the user device(s) by processing the messages, in connection with at least a portion of the context-based messaging characteristic(s), using a first set of artificial intelligence techniques; determining one or more temporal values associated with transmitting the prioritized message(s) to the user device(s) by processing the messages, in connection with the context-based messaging characteristic(s), using a second set of artificial intelligence techniques; and automatically transmitting the prioritized message(s) to the user device(s) in accordance with the temporal value(s).

What is claimed is: 
     
         1 . A computer-implemented method comprising:
 determining one or more context-based messaging characteristics for at least one user device based at least in part on message-related data associated with the at least one user device and one or more software applications running on the at least one user device;   prioritizing at least one of multiple messages intended for the at least one user device by processing the multiple messages, in connection with at least a portion of the one or more context-based messaging characteristics, using a first set of one or more artificial intelligence techniques;   determining one or more temporal values associated with transmitting the at least one prioritized message to the at least one user device by processing the multiple messages, in connection with the at least a portion of the one or more context-based messaging characteristics, using a second set of one or more artificial intelligence techniques; and   automatically transmitting the at least one prioritized message to the at least one user device in accordance with the one or more determined temporal values;   wherein the method is performed by at least one processing device comprising a processor coupled to a memory.   
     
     
         2 . The computer-implemented method of  claim 1 , wherein prioritizing at least one of multiple messages intended for the at least one user device comprises processing the multiple messages, in connection with at least a portion of the one or more context-based messaging characteristics, using at least one artificial intelligence-based classifier model to calculate at least one probability of the at least one user device acting on at least a portion of the multiple messages. 
     
     
         3 . The computer-implemented method of  claim 2 , wherein calculating at least one probability of the at least one user device acting on at least a portion of the multiple messages comprises processing the multiple messages, in connection with at least a portion of the one or more context-based messaging characteristics, using at least one gradient boosting classifier model. 
     
     
         4 . The computer-implemented method of  claim 1 , wherein determining one or more temporal values associated with transmitting the at least one prioritized message to the at least one user device comprises processing the multiple messages, in connection with the at least a portion of the one or more context-based messaging characteristics, using at least one time series algorithm. 
     
     
         5 . The computer-implemented method of  claim 1 , wherein determining one or more temporal values associated with transmitting the at least one prioritized message to the at least one user device comprises processing the multiple messages, in connection with the at least a portion of the one or more context-based messaging characteristics, using at least one neural network. 
     
     
         6 . The computer-implemented method of  claim 5 , wherein processing the multiple messages, in connection with the at least a portion of the one or more context-based messaging characteristics, using at least one neural network comprises using at least one Levenberg-Marquardt algorithm in connection with one or more of at least one gradient vector and at least one Jacobian matrix. 
     
     
         7 . The computer-implemented method of  claim 1 , wherein prioritizing at least one of multiple messages intended for the at least one user device comprises embedding at least a portion of the multiple messages to vector representations using one or more large language models (LLMs). 
     
     
         8 . The computer-implemented method of  claim 7 , wherein prioritizing at least one of multiple messages intended for the at least one user device comprises associating, using the vector representations, at least a portion of the multiple messages with one or more previous messages which received user action. 
     
     
         9 . The computer-implemented method of  claim 1 , wherein prioritizing at least one of multiple messages intended for the at least one user device comprises processing, using the first set of one or more artificial intelligence techniques, one or more delivery lists associated with the multiple messages to identify one or more recipients sharing at least one of the one or more context-based messaging characteristics for the at least one user device. 
     
     
         10 . The computer-implemented method of  claim 1 , wherein determining one or more context-based messaging characteristics for at least one user device based at least in part on message-related data comprises determining one or more context-based messaging characteristics for at least one user device based at least in part on one or more of delivery receipt data, read receipt data, and clickstream data associated with the at least one user device and the one or more software applications. 
     
     
         11 . The computer-implemented method of  claim 1 , wherein determining one or more context-based messaging characteristics for at least one user device based at least in part on message-related data comprises determining one or more context-based messaging characteristics for at least one user device based at least in part on one or more of user geo-location data, application usage data with respect to the one or more software applications, and one or more communication channel preferences with respect to the one or more software applications. 
     
     
         12 . The computer-implemented method of  claim 1 , wherein automatically transmitting the at least one prioritized message to the at least one user device comprises using at least one application programming interface (API) associated with at least one of the one or more software applications. 
     
     
         13 . The computer-implemented method of  claim 1 , further comprising:
 automatically training at least one of the first set of one or more artificial intelligence techniques and the second set of one or more artificial intelligence techniques based at least in part on feedback data related to the automatic transmitting of the at least one prioritized message to the at least one user device in accordance with the one or more determined temporal values.   
     
     
         14 . A non-transitory processor-readable storage medium having stored therein program code of one or more software programs, wherein the program code when executed by at least one processing device causes the at least one processing device:
 to determine one or more context-based messaging characteristics for at least one user device based at least in part on message-related data associated with the at least one user device and one or more software applications running on the at least one user device;   to prioritize at least one of multiple messages intended for the at least one user device by processing the multiple messages, in connection with at least a portion of the one or more context-based messaging characteristics, using a first set of one or more artificial intelligence techniques;   to determine one or more temporal values associated with transmitting the at least one prioritized message to the at least one user device by processing the multiple messages, in connection with the at least a portion of the one or more context-based messaging characteristics, using a second set of one or more artificial intelligence techniques; and   to automatically transmit the at least one prioritized message to the at least one user device in accordance with the one or more determined temporal values.   
     
     
         15 . The non-transitory processor-readable storage medium of  claim 14 , wherein prioritizing at least one of multiple messages intended for the at least one user device comprises processing the multiple messages, in connection with at least a portion of the one or more context-based messaging characteristics, using at least one artificial intelligence-based classifier model to calculate at least one probability of the at least one user device acting on at least a portion of the multiple messages. 
     
     
         16 . The non-transitory processor-readable storage medium of  claim 15 , wherein determining one or more temporal values associated with transmitting the at least one prioritized message to the at least one user device comprises processing the multiple messages, in connection with the at least a portion of the one or more context-based messaging characteristics, using at least one time series algorithm. 
     
     
         17 . The non-transitory processor-readable storage medium of  claim 14 , wherein determining one or more temporal values associated with transmitting the at least one prioritized message to the at least one user device comprises processing the multiple messages, in connection with the at least a portion of the one or more context-based messaging characteristics, using at least one neural network. 
     
     
         18 . An apparatus comprising:
 at least one processing device comprising a processor coupled to a memory;   the at least one processing device being configured:
 to determine one or more context-based messaging characteristics for at least one user device based at least in part on message-related data associated with the at least one user device and one or more software applications running on the at least one user device; 
 to prioritize at least one of multiple messages intended for the at least one user device by processing the multiple messages, in connection with at least a portion of the one or more context-based messaging characteristics, using a first set of one or more artificial intelligence techniques; 
 to determine one or more temporal values associated with transmitting the at least one prioritized message to the at least one user device by processing the multiple messages, in connection with the at least a portion of the one or more context-based messaging characteristics, using a second set of one or more artificial intelligence techniques; and 
 to automatically transmit the at least one prioritized message to the at least one user device in accordance with the one or more determined temporal values. 
   
     
     
         19 . The apparatus of  claim 18 , wherein prioritizing at least one of multiple messages intended for the at least one user device comprises processing the multiple messages, in connection with at least a portion of the one or more context-based messaging characteristics, using at least one artificial intelligence-based classifier model to calculate at least one probability of the at least one user device acting on at least a portion of the multiple messages. 
     
     
         20 . The apparatus of  claim 18 , wherein determining one or more temporal values associated with transmitting the at least one prioritized message to the at least one user device comprises processing the multiple messages, in connection with the at least a portion of the one or more context-based messaging characteristics, using at least one neural network.